Custom and finetuned embedding computation

[jhoetter]

Is your feature request related to a problem? Please describe. The creation of embeddings can range from straight-forward to super customized. Similar to labeling functions, the creation of embeddings should have a flexible interface.

Describe the solution you'd like Provide a programmatic interface for embedding calculation to enable users to build custom embeddings, and to fine-tune the models with labeled data. For instance (roughly):

from embedders.classification.contextual import TransformerSentenceEmbedder
def classification_word_a_cat_word_b_distilbert(record):
    embedder = TransformerSentenceEmbedder("distilbert-base-cased")
    return embedder.fit_transform(record["word_a_cat_word_b"], record["is_oxymoron"])

Describe alternatives you've considered see issue #24, which is an option to upload custom embeddings.

Additional context related to issue #24 - but this is related to in-app actions